Interferometric Ground Cancellation for Above Ground Biomass Estimation
Journal article, 2020

A new processing technique, i.e., ground cancellation, which removes the ground signal from a pair of interferometric synthetic aperture radar (SAR) images, is used to emphasize the response from above-ground targets. This technique is of particular interest when studying forest canopies using low-frequency signals able to reach the underlying ground, in which case the portion of the signal coming from the ground interferes with the recovery of information about the vegetation. We demonstrate that the power in ground-canceled P-band HV SAR data gives significantly higher correlations with above-ground biomass (AGB) than the interferometric images considered separately. In addition, a significant increase in the sensitivity of backscatter to AGB is observed. Ground-canceled power may then be modeled or regressed to estimate AGB; these possibilities are not discussed here as they will be the topic of forthcoming publications. The effectiveness of this technique is proven through simulations and analysis of real data gathered on tropical forests. The stability of the technique is analyzed under the digital terrain model and baseline control errors, and compensation strategies for these errors are presented.

interferometry

forest

Radar imaging

biomass

tomography

Carbon

Biomass

synthetic aperture radar (SAR)

Vegetation mapping

Azimuth

Synthetic aperture radar

Forestry

tropical

Above-ground biomass (AGB)

Author

Mauro Mariotti d'Alessandro

Polytechnic University of Milan

Stefano Tebaldini

Polytechnic University of Milan

Shaun Quegan

University of Sheffield

Maciej J. Soja

MJ Soja Consulting

University of Tasmania

Lars Ulander

Chalmers, Space, Earth and Environment, Microwave and Optical Remote Sensing

Klaus Scipal

European Space Agency (ESA)

IEEE Transactions on Geoscience and Remote Sensing

0196-2892 (ISSN) 15580644 (eISSN)

Vol. 58 9 6410-6419 9033990

Subject Categories

Probability Theory and Statistics

Signal Processing

Other Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.1109/TGRS.2020.2976854

More information

Latest update

4/5/2022 6